You can listen to recordings of each version below. Because of this, I demonstrate their use on an original version, and two remastered versions of the song, Yesterday, by the Beatles. But where I think they really shine is showing the differences between relatively similar files. These tools can compare just about any two audio files to each other. One handles the audio processing and the other helps produce comparative visualizations. If you’re interested in learning more about libroso and the ways it can help you work with audio in python, they have some great docs here.Įverything is built around two custom classes I designed for this project. I’m working in python for this project, and I use a package called Librosa and a process called FFT ( Fast Fourier Transform) to extract frequency data from my audio files. If your interested in using some of the code you see here, go checkout the github repo for this project. These can be used to see how your own masters change at various stages of the process, or even to visualize the effects of microphone placement in a space.īasically, if you’ve got two audio files, these tools give you a way to see the differences between them! Or maybe you work in the audio recording/editing industry. For the music enthusiasts here, we can use these tools to check the differences between releases of the same song (something I demonstrate in this article). These tools could be useful in many situations. In this article, I demonstrate some custom ways I created to visually compare the frequency domains of multiple audio files.
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